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Abstract:

A gastro-electrical activity mapping system and comprises a catheter
insertable through a natural orifice into the gastro-intestinal (GI)
tract and comprising an array of electrodes for contacting an interior
surface of a section of the GI tract to detect electrical potentials at
multiple electrodes, and a signal analysis and mapping system arranged to
receive and process electrical signals from multiple electrodes of the
array and spatially map GI smooth muscle electrical activity as an
activation time map, a velocity map, or an amplitude map, which may be in
the form of contour plots and may be mapped on an anatomical computer
model of at least the section of the GI tract and may be animated. A GI
mapping method and catheter are also claimed.

Claims:

1. A gastro-electrical activity mapping system comprising: a catheter
insertable through a natural orifice into the gastro-intestinal (GI)
tract and comprising an array of electrodes for contacting an interior
surface of a section of the GI tract to detect electrical potentials at
multiple electrodes, and a signal analysis and mapping system arranged to
receive and process electrical signals from multiple electrodes of the
array and spatio-temporally map wavefront propagation of GI smooth muscle
electrical activity at said section of the GI tract, over a period of
time.

2. A gastro-electrical activity mapping system according to claim 1
wherein the signal analysis and mapping system is arranged to spatially
map and visually display to a user GI electrical activity in real time or
near-real time.

3. A gastro-electrical activity mapping system according to claim 1
wherein the signal analysis and mapping system is arranged to map GI
electrical activity as an activation time map of the GI electrical
activity.

4. A gastro-electrical activity mapping system according to claims 1
wherein the signal analysis and mapping system is arranged to map GI
electrical activity as a velocity map indicative of the direction and
speed of the GI electrical activity.

5. A gastro-electrical activity mapping system according to claim 1
wherein the signal analysis and mapping system is arranged to map GI
electrical activity as an amplitude map of the amplitude of the GI
electrical activity.

6. A gastro-electrical activity mapping system according to claim 1
wherein the signal analysis and mapping system is arranged to map the GI
electrical activity as a contour plot of the GI electrical activity.

7. A gastro-electrical activity mapping system according to claim 1
wherein the signal analysis and mapping system is arranged to map the GI
electrical activity on an anatomical computer model of at least the
section of the GI tract.

8. A gastro electrical activity mapping system according to claim 7
wherein the signal analysis and mapping system is arranged to map the GI
electrical activity on a patient specific anatomical model of at least
the section of the GI tract.

9-11. (canceled)

12. A gastro-electrical activity mapping system according to claim 1
wherein the signal analysis and mapping system is arranged to register
the electrode array of the catheter on the anatomical model.

13-14. (canceled)

15. A gastro electrical activity mapping system according to claim 1
wherein the signal analysis and mapping system is arranged to map the GI
electrical activity as an animation.

16. (canceled)

17. A gastro-electrical activity mapping system according to claim 1
wherein the signal analysis an processing system is arrange to analyse
the GI electrical activity for events indicative of GI slow waves and
then to cluster the detected events into groups each relating to a common
GI slow wave base on temporal closeness.

18. A gastro-electrical activity mapping system according to claim 17
wherein the signal analysis an processing system is arrange to analyse
the GI electrical activity for events indicative of slow waves by falling
edge detection and a time varying threshold.

19. A gastro-electrical activity mapping system according to claim 18
wherein the falling edge detection comprises convolving the GI electrical
activity with an edge detecting kernel.

20-22. (canceled)

23. A gastro-electrical activity mapping system according to claim 17
wherein the signal processing and mapping system is arrange to cluster
the detected events by a region growing using polynomial surface estimate
stabilization method.

24. A gastro-electrical activity mapping system according to claim 23
arrange to cluster detected events by selecting a master electrode,
retrieving a list of events detected at the master electrode as master
seeds, for each master seed creating a queue of events detected at nearby
electrodes, and spatiotemporally filtering each queue of detected events.

25-32. (canceled)

33. A gastro-electrical activity mapping system according to claim 1
wherein the signal processing and mapping system is arranged to quantify
averages of any one or more of GI electrical activity propagation
directions, normal versus abnormal propagation, frequencies, regional
stomach velocities, or amplitudes, an report an average figure and/or
average map for a recording period.

34. A gastro-electrical activity mapping system according to claim 1
wherein the signal processing and mapping system is arrange to identify
an report abnormal GI electrical activity.

35. A gastro-electrical activity mapping system according to claim 1
wherein the catheter comprises an electrode carrier carrying on an
exterior surface the array of electrodes and expandable when in place to
cause the electrodes to contact the interior surface of the GI tract.

36-39. (canceled)

40. A gastro-electrical activity mapping system according to claim 1
wherein the electrodes are point electrodes to indent the mucosa of the
interior surface of the section of the GI tract to enhance electrical
contact.

41. A gastro-electrical activity mapping system according to claim 1
wherein the catheter comprises between 3 and 10 rows of electrodes each
space lengthwise of the catheter, an each row comprising between 3 and 10
electrodes.

42-47. (canceled)

48. A method for mapping GI electrical activity which comprises inserting
a catheter through a natural orifice into the GI tract an causing an
array of electrodes of the catheter to contact an interior surface of a
section of the GI tract to detect electrical potentials at multiple
electrodes, an receiving an spatio-temporally mapping wavefront
propagation from the electrical signals GI electrical activity at said
section of the GI tract, over a period of time.

49. A method according to claim 48 including mapping GI electrical
activity as an activation time map.

50. A method according to claim 48 including mapping GI electrical
activity as a velocity map indicative of the direction and speed of the
GI electrical activity.

51. A method according to claim 48 including mapping GI electrical
activity as an amplitude map indicative of the amplitude of the GI
electrical activity.

52. A method according to claim 48 including mapping the GI electrical
activity as a contour plot of the GI electrical activity.

53. A method according to claim 48 including mapping the GI electrical
activity on an anatomical computer model of at least the section of the
GI tract.

54. A method according to claim 53 including mapping the GI electrical
activity on a patient-specific anatomical model of at least the section
of the GI tract.

55. A method to claim 48 including analysing the GI electrical activity
for events indicative of GI slow waves an clustering detected events into
groups each relating to a common slow wave base on temporal closeness.

56. A method according to claim 55 including analysing the GI electrical
activity for events indicative of slow waves by falling edge detection
and a time varying threshold.

57-60. (canceled)

61. A method according to any of claim 55 including clustering detected
events by a region growing using polynomial surface estimate
stabilization method.

62-72. (canceled)

73. A catheter for mapping GI electrical activity, insertable through a
natural orifice into the GI tract an comprising an array of sufficient
point electrodes arrange to contact around and/or along an interior
surface of a section of the GI tract to detect electrical potentials to
enable mapping of electrical activity at said section of the GI tract.

74. A catheter according claim 73 which comprises an electrode carrier
carrying on an exterior surface the array of electrodes an expandable
when in place to cause the electrodes to contact the interior surface of
the GI tract.

75. A catheter according to claim 74 wherein the expandable electrode
carrier is expandable by fluid inflation.

76. A catheter according to claim 74 wherein the expandable electrode
carrier comprises an expandable mesh.

77. A catheter according to claim 76 wherein the expandable mesh is
resilient with a memory for its expanded condition.

78. (canceled)

79. A catheter according to claim 73 wherein the electrodes indent the
mucosa of the interior surface of the section of the GI tract to enhance
electrical contact.

80. (canceled)

81. A catheter according to claim 73 herein the array of electrodes
comprises between 9 and 120 electrodes.

82. A catheter according to claim 73 wherein the electrodes comprise
conductive protrusions of length between about 2 and about 5 mm.

83. A catheter according to claim 73 wherein the electrodes comprise
conductive protrusions of length between about 2 and about 3 mm.

84. A catheter according to claim 73 wherein the electrodes comprise
conductive protrusions of cross-sectional dimension between about 0.3 and
about 3 mm.

85. A catheter according to claim 73 wherein the electrodes comprise
conductive protrusions of cross-sectional dimension between about 0.5 and
about 1.5 mm.

86. A catheter according to claim 73 wherein the electrodes comprise
conductive protrusions of cross-sectional dimension between about 0.7 and
about 1 mm.

87. A method for detecting GI slow wave activations in GI electrical
activity which includes analysing the GI electrical activity for events
indicative of GI slow waves and clustering detected events into groups
each relating to a common slow wave based on temporal closeness.

88. A method according to claim 87 including analysing the GI electrical
activity for events indicative of slow waves by falling edge detection
and a time varying threshold.

89. A method according to claim 88 wherein the falling edge detection
comprises convolving the GI electrical activity with an edge detecting
kernel.

90. A method according to claim 88 wherein the time-varying threshold is
calculated by a moving median window.

91-92. (canceled)

93. A method according to claim 88 including clustering detected events
by a region growing using polynomial surface estimate stabilization
method.

94. A method according to claim 93 including clustering detected events
by selecting a master electrode, retrieving a list of detected events at
the master electrode as master seeds, for each master seed creating a
queue of events detected at nearby electrodes, and spatiotemporally
filtering each queue of detected events.

95. A method according to claim 94 wherein including initialising a new
cluster for each of the detected events at the master electrode.

96. A method according to claim 93 including counting the number of
detected events in the cluster and generating a second order polynomial
surface when the number of detected events in the cluster is greater than
a critical mass.

97. A method according to claim 96 wherein the second order polynomial
surface acts as the spatiotemporal filter.

98-102. (canceled)

103. A method for clustering detected GI slow wave events in GI
electrical activity into groups each relating to a common slow wave base
on temporal closeness, which comprises clustering detected events by a
region growing using polynomial surface estimate stabilization method.

104. A method according to claim 103 including clustering detected events
by selecting a master electrode, retrieving a list of detected events at
the master electrode as master seeds, for each master seed creating a
queue of events detected at nearby electrodes, an spatiotemporally
filtering each queue of detected events.

105. A method according to claim 104 wherein including initialising a new
cluster for each of the detected events at the master electrode.

106. A method according to claim 103 including counting the number of
detected events in the cluster an generating a second order polynomial
surface when the number of detected events in the cluster is greater than
a critical mass.

107-112. (canceled)

Description:

FIELD OF INVENTION

[0001] The invention relates to a system and method for mapping
gastro-intestinal electrical activity.

BACKGROUND

[0002] Gastric dysrhythmias underlie or contribute to diseases including
gastroparesis, functional dyspepsia, and gastro-esophageal reflux disease
(GERD). Gastroparesis is a condition in which the stomach typically fails
to empty properly after a meal, leading to symptoms of early fullness,
bloating, pain, nausea, vomiting and malnutrition and possibly death in
severe cases. Medical guidelines suggest that the majority of patients
with suspected gastroparesis should receive an upper gastrointestinal
(GI) endoscopy study (a video-guided examination of the inside of the
stomach). Functional dyspepsia is a condition characterised by symptoms
of `chronic indigestion` lasting at least weeks to months, which may
include bloating, nausea, and pain after eating. The causes of functional
dyspepsia are not well understood, however dysrhythmic gastric activity
has been clearly implicated, with up to 60% of adult dyspeptic patients
showing abnormal gastric electrical activity. Delayed gastric emptying
occurs in 25-40% of functional dyspepsia. Upper GI endoscopy is a
standard diagnostic tool for assessing patients presenting with
dyspepsia. Delayed gastric emptying also affects a significant
sub-population of patients with GERD, and gastric dysrhythmia has been
implicated.

[0003] Peristaltic activity in the GI tract is coordinated by a
propagating electrical activity termed slow waves. GI slow waves are
initiated and spread via networks of interstitial cells of Cajal (ICCs),
which are coupled to the smooth muscle layers in the GI tract wall. In
the human stomach, slow waves originate at a pacemaker site high on the
greater curvature, and propagate toward the antrum at a normal frequency
of approximately three cycles per minute.

[0004] Electrocardiography (ECG) is a routine diagnostic test for cardiac
dysrhythmias, in which electrodes are placed on the skin to record the
distant organ electrical activity. Electrogastrography (EGG) or the
assessment of GI electrical activity through skin electrodes has also
been proposed but despite research efforts has failed to meet clinical
expectations, partly because the quality of GI electrical signals
recorded at the skin is too limited to provide accurate diagnostic value.
Also, EGG is a summation of all of the electrical activity occurring in
the stomach and so cannot provide accurate information regarding the
normal or abnormal propagation of the individual slow wave cycles.

[0005] A SQUID (Super Quantum Interference Device) can be used to measure
the magnetic fields associated with GI electrical activity, but is a
multi-million dollar device that must also be housed in a
magnetically-shielded room, and analysis of the signals obtained is
complex and has not yet been reliably achieved. Also, the resolution
achieved via a SQUID may be suboptimal.

[0006] A roving electrode placed into sequential sites on the mucosa of
the stomach, or a small number of electrodes linearly arranged and
attached to a naso-gastric tube, can give some indication of GI
dysrhythmic activity, however may not reliably provide information on the
spatial propagation of gastric slow wave activity and therefore cannot
describe abnormal velocities, propagation directions, or dysrhythmias
accurately.

[0007] High-resolution mapping of GI electrical activity by measurement at
the serosal surface requires invasive surgical access and therefore is
not appropriate for use in the vast majority of patients with
gastrointestinal symptoms.

SUMMARY OF INVENTION

[0008] In broad terms in one aspect the invention comprises a system for
mapping gastro-electrical activity comprising: [0009] a catheter
insertable through a natural orifice into the gastro-intestinal (GI)
tract and comprising an array of electrodes for contacting an interior
surface of a section of the GI tract to detect electrical potentials at
multiple electrodes, [0010] a processing system arranged to receive and
process electrical signals from multiple electrodes of the array and
spatially map the GI smooth muscle electrical activity at said section of
the GI tract.

[0011] In some embodiments the system is arranged to visually display a
map or animation of GI electrical activity in real time.

[0012] In some embodiments the system is arranged to display any one or
more of an activation time map indicative of the propagation of
electrical activity, a propagating wavefront animation, a velocity map
indicative of slow wave velocity and/or direction, an amplitude map of
slow wave signal amplitudes across the stomach, and a dysrhythmia map of
the GI electrical activity.

[0013] In some embodiments the system is arranged to map the GI electrical
activity on to a generic or a subject-specific anatomical model of the
section of the GI tract.

[0014] In some embodiments the system may be arranged to determine or
approximate the relative locations of electrodes of the array in contact
with the interior surface of the section of the GI tract, to develop or
modify an anatomical model of the section of the GI tract, and to map the
GI smooth muscle electrical activity onto the anatomical model.

[0015] In some embodiments the system may comprise a reference database
indicative of geometries of one or more sections of the GI tract and
related characteristics such as subject height and sex relating to each
geometry, and the system is arranged to select a best-fit geometry from
the database for each subject under study and optionally modify the
selected geometry.

[0016] In broad terms in a further aspect the invention comprises a method
for mapping GI electrical activity which comprises inserting a catheter
through a natural orifice into the GI tract and causing an array of
electrodes of the catheter to contact an interior surface of a section of
the GI tract to detect electrical potentials at multiple electrodes, and
receiving and spatially mapping from the electrical signals GI electrical
activity at said section of the GI tract.

[0017] In a preferred form said processing of the electrical potential
signals detected at the electrodes includes amplifying and/or filtering
the signals, identifying slow waves, and animating the individual
propagating waves over a generic or subject-specific anatomical model.

[0018] The processing may also include making time activation maps of
waves, calculating velocity and amplitude fields from the activation
maps, and displaying the activation maps and velocity fields over the
anatomical model.

[0019] The processing may also include quantifying averages of any one or
more of propagation directions, normal versus abnormal propagation, types
of dysrhythmias, frequencies, regional stomach velocities, amplitudes,
and reporting average figures and/or representing an average map of a
recording period.

[0020] The processing may also include comparing the GI electrical
activity to a stored reference database to provide an indication of
normal or abnormal GI electrical activity.

[0021] In broad terms in a further aspect the invention comprises a
catheter for mapping GI electrical activity, insertable through a natural
orifice into the GI tract and comprising an array of sufficient
electrodes arranged to contact around and/or along an interior surface of
a section of the GI tract to detect electrical potentials to enable
mapping of electrical activity at said section of the GI tract.

[0022] In some forms the catheter comprises an inflatable or otherwise
expandable electrode carrier such as a balloon or expandable mesh,
carrying on an exterior surface the array of electrodes, the electrode
carrier being inflatable or expandable via the catheter when in place to
cause electrodes to contact the interior surface of the GI tract. The
catheter may also comprise a tube or other element that extends
internally towards the distal end of the catheter to assist in locating
the catheter in the desired location in the GI tract.

[0023] The invention includes an inflatable or expandable balloon or mesh
or other attachable electrode carrier end for a catheter for mapping GI
electrical activity, attachable to an end of the catheter, and inflatable
or expandable through the catheter when in place, the catheter end
comprising the array of electrodes for contacting the interior surface of
the GI tract.

[0024] The system and method of the invention are intended to be useful in
the diagnosis of gastric dysrhythmias including in gastroparesis and
functional dyspepsia, and may also be useful in the diagnosis of disease
mechanisms in gastro-oesophageal reflux disease and other
gastro-intestinal motility disorders such as small intestinal, colonic
and rectal dysmotility disorders, or in other smooth-muscle-lined
viscera, including the bladder.

[0025] The system of the invention may be employed as an adjunct to upper
or lower GI endoscopy.

[0026] The system and method of the invention may be useful to guide
therapies for gastric dysmotility disorders, including gastric electrical
stimulation, targeted ablation of aberrant conduction pathways and
targeted drug delivery.

[0027] In broad terms in a further aspect the invention comprises a method
for detecting GI slow wave activations in GI electrical activity which
includes analysing the GI electrical activity for events indicative of GI
slow waves and clustering detected events into groups each relating to a
common slow wave based on temporal closeness.

[0028] In broad terms in a further aspect the invention comprises a method
for clustering detected GI slow wave events in GI electrical activity
into groups each relating to a common slow wave based on temporal
closeness, which comprises clustering detected events by a region growing
using polynomial surface estimate stabilization method.

[0029] The term "comprising" as used in this specification means
"consisting at least in part of". When interpreting each statement in
this specification that includes the term "comprising", features other
than that or those prefaced by the term may also be present. Related
terms such as "comprise" and "comprises" are to be interpreted in the
same manner.

BRIEF DESCRIPTION OF THE FIGURES

[0030] Embodiments of the invention are further described with reference
to the accompanying figures, without intending to be limiting, in which:

[0048] FIG. 18 shows one electrode channel of GI slow wave data recorded
from the serosal surface of the GI tract, referred to in the subsequent
description of experimental work,

[0049] FIG. 19 shows two channels of GI slow wave activity and stimulation
artifact recordings from the mucosal gastric surface, as referred to in
the subsequent description of experimental work,

[0050]FIG. 20 shows GI slow wave activity from three electrodes, referred
to in the subsequent description of experimental work,

[0051] FIGS. 21a and b show a spatial activation maps from two mucosal
recordings of consecutive GI slow waves, referred to in the subsequent
description of experimental work,

[0052] FIG. 22 shows the points at which the stomach was measured during
surgery to reconfigure a anatomical model to be subject specific,
referred to in the subsequent description of experimental work, and

[0053] FIGS. 23 to 26 show activation time and velocity maps of gastric
electrical activity, referred to in the subsequent description of
experimental work.

DETAILED DESCRIPTION OF EMBODIMENTS

[0054] GI Mapping Catheter

[0055] FIGS. 1 and 2 show one form of a mapping catheter useful for
mapping GI electrical activity. The catheter comprises an array of
electrodes some indicated at 1 spaced around an expandable electrode
carrier comprising an inflatable balloon 2, attached to a nasogastric or
oral gastric or similar tube 3. Signal wires or conductors (electrically
insulated) one from each electrode 1 pass through the tube 3 from the
catheter to exit the proximal end of the nasogastric tube, for example at
a plug for coupling the signal lines to electronic instrumentation. FIG.
1 shows the balloon electrode carrier 2 deflated and FIG. 2 shows it
inflated.

[0056] In use the catheter with the balloon 2 deflated is intubated
temporarily via a natural orifice, such as via the mouth, into the GI
tract and when in position at the desired location, such as in the
gastric antrum, gastric corpus, upper small bowel, rectum, large bowel,
or bladder, is expanded by inflation through the lumen of the tube 3
until the electrodes 1 or at least some electrodes contact the mucosal
surface that part of the GI tract. The catheter may also comprise a
second internal catheter tube (which may alternatively serve for
inflation of the balloon) or other element that extends through the tube
3 to within the balloon 2, as indicated at 4 in phantom outline in FIG.
3, to assist in locating the tip of the balloon in the desired position.
FIG. 3 shows the GI mapping catheter positioned in the gastric antrum
indicated at G and before inflation, and FIG. 4 shows the catheter after
inflation to cause multiple electrodes 1 to contact the mucosal surface
around the interior of and spaced lengthwise of the GI tract, sufficient
to obtain electrical potentials indicative of GI electrical activity
around and lengthwise of that part of the tract. The electrodes are
preferably but not exclusively point electrodes, such as convex pointing
electrodes, which at least when the balloon 2 is inflated stand
perpendicular to the surface of the balloon, such that they indent the
mucosa to enhance contact and signal quality.

[0057]FIG. 5 shows an alternative form of catheter which comprises
multiple fold-out resilient electrode carrying elements such as metal
wires 6 from around the catheter end, the ends of which carry or comprise
the electrodes 1. At insertion the elements 6 are retained folded tightly
against the end of the catheter against their natural resilience for
example by an external cover (not shown) which can be drawn back up the
catheter remotely after positioning of the catheter, to allow the
resilient electrode carrying elements to spring or fold out to-push the
electrodes 1 against the mucosal surface, again around and lengthwise of
that part of the GI tract. The fold out elements 6 may optionally be
ordered in series of circular rows around and spaced along the catheter
end, which may be connected so that each row in use folds out like an
umbrella, or the elements may be otherwise regularly (or irregularly)
spaced around and along the catheter end.

[0058] FIGS. 6 and 7 show a further alternative form of GI mapping
catheter comprising an expandable mesh 5, carrying a similar array of
spaced electrodes some indicated at 1. The catheter mesh 5 may be formed
of a resilient plastics material or a spring metal such as surgical grade
stainless steel, and having a memory for its expanded position, which is
mechanically restrained unexpanded as shown in FIG. 7 until in position
within the GI tract for example by a covering sleeve 8 which can then be
withdrawn remotely by the clinician to the position of the sleeve shown
in FIG. 6 to allow the mesh catheter to resiliently expand as shown in
FIG. 6 to press the catheter electrodes against the interior of the GI
tract. In this and all embodiments expansion, and contraction for
withdrawal, of the catheter may be initiated or controlled by a trigger
or other device on a handle or control, to which the catheter is
connected by the tube 3, through which one or more control lines or
similar pass to the catheter and/or surrounding sleeve. FIG. 6 shows the
catheter in position in the gastric antrum and FIG. 7 shows the catheter
unexpanded and within contraction sleeve 8. Rows or another array of
electrodes 1 are spaced around and lengthwise of the expandable mesh 5.
As before the electrodes 1 are preferably point electrodes, which at
least when the catheter is expanded stand perpendicular to the catheter
surface, to indent the mucosa to enhance contact and signal quality. The
electrodes 1 may be carried by the mesh 5 so that during intubation of
the catheter the electrodes lay against or adjacent the catheter mesh and
after the catheter has been positioned in the desired part of the GI
tract, may be caused to move to protrude outwardly from the carrier mesh,
to press against the gastric mucosa. The sleeve 8 typically in the form
of a sock of a relatively rigid plastics material and as long as the
catheter itself, surrounds the catheter when the catheter is unexpanded
so that the catheter is contained within the sleeve. The catheter may be
intubated to the desired position unexpanded as shown in FIG. 7 then
before expansion of the mesh catheter (or inflation of a balloon
catheter), or after only partial expansion of the catheter, folding or
pivoting electrodes 1 may be caused to move to their protruding or
contact position following which the sleeve 8 may be withdrawn so that
the catheter is caused to expand fully to cause the outwardly facing
electrodes to then contact the interior of the GI tract.

[0059] In yet another embodiment a mesh catheter such as described in
relation to FIGS. 6 and 7 may comprise a balloon within, which is
inflated in use to expand the mesh catheter and press the electrodes
against the mucosal surface. Electrodes 1 may each be mounted for
reciprocal protrude-withdraw movement within a small outwardly facing
cylinder carried by the mesh, so that full expansion of the balloon
within the mesh will both expand the mesh fully and also push the
electrodes from within the mesh to protrude. Each electrode mounting may
comprise a small recoil spring arranged to withdraw the electrode when
the balloon is deflated for withdrawal of the catheter from the patient.

[0060] FIGS. 8a-c show a single electrode 1, which is mounted to the
catheter 5 via a small coil spring 9. In the example shown the catheter
is a mesh catheter as previously described and each or many electrodes
may be mounted individually at intersections of individual mesh elements
5a-5c (as are other electrodes of the catheter--only one being shown in
FIG. 8). When the catheter is within the sleeve 8 each electrode 1 is
bent over as shown in FIG. 8a against the mesh, allowed by the spring
mounting described. When the catheter within the sleeve has been
intubated to the desired position within the GI tract and the sleeve is
withdrawn sufficiently i.e. the sleeve 8 moves in the direction of arrow
A in FIG. 8a, the electrodes 1 stand up perpendicular to the mesh 5 and
press against the mucosa, as shown in FIG. 8b. The springs 9 are
sufficiently strong and resilient to cause the electrodes to so move.
Subsequently when the catheter is to be withdrawn, initial withdrawal of
the movement of the catheter, in the direction of arrow B in FIG. 8c,
causes the catheter to move relative to the sleeve and the catheter to be
drawn back into the sleeve 8 causing the electrodes 1 to be folded or
bent down as shown in FIG. 8c, all to their starting position when the
catheter is again fully home within the sleeve. In alternative
embodiments the electrodes may be mounted to the mesh or electrode
carrier of the catheter in another form, instead of by a spring mounting
as described, by a pivot mount to the catheter. In the embodiment of FIG.
8 the spring 9 instead of a small coil spring may comprise a single
resilient element of spring stainless steel or a resilient plastics
material, for example.

[0061] For example an electrode array of a GI mapping catheter of the
invention may comprise between 3 and 10 rows of electrodes spaced
lengthwise of the catheter between the proximal end (coupled to tube 3)
and the distal end, each row comprising between 3 and 10 electrodes
spaced around the catheter, providing an array of between 9 and 100
electrodes for example. In an alternative embodiment the electrodes 1 may
be arranged in rows angled or tangential to the longitudinal axis of the
catheter, with, when the catheter is an expanding mesh catheter, an
electrode at each or at least many intersections of mesh elements, over a
part of the major surface area of the mesh catheter.

[0062] In relation to the electrode form, desired qualities for GI
electrical signals acquired by the electrodes are an adequate signal to
noise ratio (SNR) (the gastric mucosa has high impedance and attenuates
signal), a stable baseline, and preferably a steep negative descent at
the down-slope of the slow wave signal. As stated the electrodes are
preferably protruding, to press into or indent the mucosa to achieve an
adequate SNR. Smaller electrode diameters will generally achieve a
steeper down-slope (shorter duration of activation over the electrode
signal; quicker offset to onset period). However, if the electrodes are
too protruding and of too small a diameter, they may puncture the gastric
mucosa rather than press into it. A suitable form electrode may comprise
a conductive protrusion of between 2 and 5 mm, or 2 and 3 mm, or about
2.5 mm in length (from the electrode carrier or electrode base to the tip
of the electrode), and of a cross-sectional dimension (such as diameter
if the electrodes have a circular or similar cross-section) of between
0.3 and 3 mm, or 0.5 and 1.5 mm, or 0.7 and 1 mm, or about 0.8 mm. The
electrodes may suitably comprise sintered Ag--AgCl electrodes.

[0063] GI Mapping System and Method

[0064] In use a GI mapping catheter as described is connected by a cable
to a signal acquisition stage of a GI electrical activity mapping system
of the invention and once the GI catheter is positioned by the clinician
in the GI tract, and engaged with the mucosal wall, the clinician may
activate signal acquisition, typically via a graphical user interface.
The GI mapping system is arranged to receive and process multi-channel
electrical signals from the mapping catheter electrodes 1, either all or
at least those making good contact, and is arranged to identify GI slow
waves and spatially map the GI myenteric electrical activity (herein
referred to as GI smooth muscle or slow wave electrical activity)
preferably in real time or near-real time. The system may typically
comprise a computer including a processor, program memory, and an
operator interface including display or VDU which may be a touch-input
screen and optionally also a keyboard or keypad, and a communications
interface, coupled by a data bus.

[0065] The analysis processing by the GI mapping system of the electrical
potential signals detected at the electrodes includes identifying GI
electrical slow waves and mapping the electrical activity, which may
include producing any one or more of an activation time map or maps of
gastric electrical waves or wavefronts, a velocity field map or maps, an
amplitude map or maps, all either as pixelated or isochronal maps or in
other form, and which may also or alternatively animate any one or more
of the same and/or GI slow wave propagation generally. The analysis
processing may include mapping and/or animating the GI electrical
activity or propagating waves over a generic or subject-specific
anatomical model, running on the system processor.

[0066] The GI mapping system may also be arranged to carry out analysis
processing including identifying any one or more of normal versus
abnormal propagation or amplitudes, and dysrhythmias including focal
activities, re-entrant loops, mechanisms of bradygastrias and
tachygastrias and fibrillation for example. Thus analysis processing may
also include comparing the mapped GI electrical activity to a stored
reference database to provide an indication of normal or abnormal GI
electrical activity.

[0067]FIG. 9 shows an example of a user-display on a VDU 20 that a GI
mapping system of the invention may present to a clinician during an
examination. On the upper right indicated at 21 is a live video-endoscopy
view of the gastrointestinal tract lumen. On the upper left indicated at
22 is a view of a generic or optionally subject-specific anatomical
computer model of the section of the GI tract, over which the GI
electrical activity or slow wave information obtained from the electrode
array is mapped and may be animated. The live electrical potentials from
a selection of channels from the electrode array are shown at 23. The
system may be arranged to determine or approximate the relative locations
of the electrodes in contact with the interior surface of the GI tract,
to register same correctly to the model and optionally to develop or
modify the model. The system may be arranged to display gastroscopic view
21 initially full screen, and after the mapping catheter is inserted and
expanded the gastroscopic view may be reduced to the window 70 or closed,
the electrophysiological recordings, and mapped electrophysiological data
such as activation time map(s), velocity map(s), amplitude map(s),
dysrhythmia map(s), and/or other wavefront propagation displayed as 2D or
3D images and/or animations shown in real-time. The system of the
invention may also be arranged to record the session or to communicate
the GI electrical data to another system for offline or further analysis
and/or storage.

[0068]FIG. 10 shows another example of or an additionally available user
display of a GI mapping system of the invention. A representation of an
anatomical model of a stomach shape (or part thereof) is indicated at 31.
The position of the electrodes of the array on the model (for example,
for selecting channels to view) is indicated at 32. The electrode
positions may be numbered. An activation time map which comprises
isochronal propagation of GI slow waves on the stomach model is indicated
at 33. An isochronal map comprises a two-dimensional contour plot showing
the spatiotemporal sequence of GI slow wave activation. A velocity map
which comprises multiple individual vectors on the model indicates the
velocity and direction of GI slow wave propagation at each electrode is
indicated on the model at 34.

[0069] The system may be arranged to produce and display and optionally
animate on a model in 3D the GI electrical activity map(s).

[0070] In FIG. 10, in the activation time map and velocity map at windows
33 and 34 the gastric electrical activity is shown propagating normally.
FIGS. 11a and 11b show respectively similar activation time and velocity
maps in which in contrast a GI slow wave is looping and propagating
abnormally.

[0071]FIG. 12 is a flow chart illustrating signal analysis, mapping, and
model fitting stages of a preferred embodiment of the invention. The
darkest outline boxes indicate key user inputs, medium outline boxes
indicate key integrated outputs, and lightest outline boxier indicate
computer processing steps. After positioning a GI catheter and recording
or beginning to record electrical signals from the electrodes, and any
amplifying, filtering, and baseline correction, GI electrical slow wave
events at electrodes are marked, and clustered or partitioned into
clusters of electrical events each relating to a discrete GI electrical
slow wave cycle.

[0072] One or more of velocity calculations, amplitude calculations, and
isochrone map calculations are performed by the system processor. The
resulting activation time, velocity, and amplitude information may then
be spatially mapped in 2D or 3D in pixelated or isochronal or other form,
optionally on a generic or subject-specific computer model of the GI
tract or the part thereof. The model may be a stored generic model or one
of a number of stored generic models of the GI tract or a part thereof,
or may be constructed from a subject's specific anatomical images of the
GI tract acquired prior to the EGG examination, for example via MRI or CT
scanning. The catheter position and degree of expansion and thus
individual electrode positions are registered on the map or model and the
velocity, amplitude, and/or isochrone data fitted to the map or model,
and displayed to the clinician on a VDU as 2D or 3D maps or animations. A
wavefront propagation animation may be produced from the marked or marked
and clustered GI slow wave events and also displayed. The system may be
arranged to compare the mapped GI electrical activity to a database, and
a clinician may interface with the system via a touch screen, keypad,
computer mouse or similar through an appropriate menu or non-menu based
interface system. The clinician may use the resulting analysis to effect
targeted therapy for the patient.

[0073] Many of individual system blocks of the preferred embodiment system
of FIG. 12 are now described in further detail.

[0074] Signal Recording

[0075] Signal acquisition may for example be at a sampling resolution of
>1 Hz, typically at ˜30 Hz, and up to 512 Hz or greater. In a
signal acquisition stage the signal channels may be digitized and
amplified, and filtered to remove low frequency drift and wandering
baselines, important for mucosally-acquired low amplitude and low
frequency GI electrical signals, and to remove unwanted artifacts and
noise.

[0076] Automated Activation Time Marking

[0077] "Activation" as used herein refers to a rhythmic spontaneous inward
current in interstitial cells of Cajal, causing the cell membrane
potential to rapidly rise. In extracellular recordings the onset of this
depolarization termed "activation time" or AT signals the arrival of a
propagating electrical wavefront to a particular location in the tissue.
ATs must be identified ("marked") at each electrode site. The marked
electrode ATs are used to generate an activation time map or maps which
provide(s) detailed spatiotemporal visualization of the spread of GI
electrical activity across an area of tissue. ATs are identified to
produce an activation time map or animation.

[0078] A preferred method for automated AT marking is a falling edge
varying threshold method, which comprises transformation, smoothing,
negative edge detection, time-varying threshold detection, and AT marking
of the signal from each electrode. FIG. 13 is a flow chart of a preferred
embodiment of an FEVT method for GI slow wave activation time
identification.

[0079] Transformation can be carried out by for example negative
derivative, amplitude sensitive differentiator transformation, non-linear
energy operator transformation, or fourth-order differential energy
operator transformation. A moving average filter of a tunable width is
applied to the transformed signal to smooth the signal. The
transformation amplifies the relatively large amplitude, high frequency
components in the recorded signal, which corresponds to the onset of
activation. Subsequent filtering increases the SNR of the transformation
by reducing high frequency noise.

[0080] An edge detector kernel is then be used to identify falling edges
within the smoothed signal. A falling edge produces a positive deflection
in the signal from the edge detector kernel, and a rising edge produces a
negative deflection.

[0081] A FEVT signal is then calculated by multiplying the signal from a
falling-edge detector and the smoothed signal, and then all negative
values which indicate a rising edge are set to 0.

[0082] In the preferred form a time-varying threshold is calculated from
the FEVT output, by computing the median of the absolute deviation in a
moving window of predefined width. The centre of the moving window
consecutively shifts one sample forward, such that the threshold is
computed for each point in time over the duration signal. Such a variable
threshold improves detection accuracy by accounting for slight deviations
in the waveforms of recorded signals. A constant threshold may be used
but a time-varying threshold may reduce potential double counting and
mis-marking. Signal values greater than or equal to the threshold define
the times at which slow wave events might occur.

[0083] Individual slow wave events are then identified from the resulting
data set which may contain multiple slow wave events, by imposing a
criterion that distinct events must be separated by a minimum time.

[0084] Automated GI Slow Wave Cycle Clustering

[0085] The ATs as are clustered based on temporal closeness, into distinct
cycles that partition the discrete propagating GI slow wave wavefronts.
Clustering identifies individual GI slow waves based on a temporal
closeness criterion, and proceeds in iterative fashion. Consecutive
members in a data set are grouped as representing the same GI slow wave
event if they are close enough in time to an estimated activation time.
Such estimation employs deriving the best-fit second order polynomial
surface, based on the location of electrode sites and the activation
times detected at them. The estimated activation time is computed by
extending said polynomial surface to the candidate location for
clustering. The maximum time difference allowed to cluster two members is
termed the time tolerance; its value must be long enough to accommodate
small estimation errors and identify fractionated waveforms as single
events, but short enough to properly partition distinct GI slow waves.
When no more members of the data set meet this closeness criterion, a new
cluster is formed to represent the next GI slow wave event. Auto
clustering groups all marked data into individual clusters, each
delimiting an independent GI slow wave event

[0086] FIG. 14 is a flow chart of a preferred embodiment clustering method
termed region growing using polynomial surface estimate stabilization
(REGROUPS) for clustering (x, y, t) points representing ATs into groups
representing independent GI slow wave cycles, where (x, y) denotes the
position of an electrode site and t denotes an AT marked at that site,
and t denotes the activation times identified at that site.

[0087] The algorithm is initialized by automatically selecting a "master
seed", which is an electrode position embedded in a region with the
maximal density of information about a propagating wavefront. The cluster
is then grown outward from the region where the spatial density of data
is highest, ensuring that the subset of points initially assigned to the
cluster is statistically cohesive and limiting the possibilities of
assigning noise signals to a nascent clusters. The master seed may be
selected by first calculating the total number of ATs detected at each
electrode site, then finding the centre of mass and selecting the seed
location as the electrode closest to the centre of mass. Once the master
seed is located, a queue containing the nearby electrode sites' ATs in a
specified circular range of the master seed is created and the first AT
in the queue becomes the current seed. Each AT is tested for membership
of a cluster based on comparison to an estimated AT, which is derived by
fitting (in the least squares sense) a second-order polynomial surface to
the data points already assigned to the cluster. The 2nd order
surface acts as a continuously updating spatiotemporal filter: if the
time difference of estimated AT and tested AT is small enough, then the
tested AT is considered as representing a same wavefront as the seed and
is assigned to the cluster. Once assigned, the point is not assessed
again. If the tested point is clustered, all of its neighbour electrodes
and marked ATs at these electrodes are added to the back of the queue,
providing they are not already in it. If a tested point is not clustered,
it may be tested again for membership only after a new cluster is
initialized at the next iteration. This restriction forces all wavefronts
to be independent. Regardless of whether any point is added to the
cluster, the current seed is removed from the queue and the next
electrode site becomes the current seed. Thus, the region in (x, y, t)
space representing an independent cycle grows, and terminates when the
queue of nearby points becomes empty. At this stage, the cluster contains
all ATs from one GI slow wave cycle. The same process is repeated to
identify another independent cycle, starting with the next sequential AT
marked at the master seed. Each iteration produces a cluster of (x, y, t)
points which represent the dynamics of an independent GI slow wave cycle,
from which wave front propagation, an actuation time map may be produced,
and isochrones map calculation, velocity and amplitude calculation can
all be realized.

[0088] Activation Time or Isochronal Mapping

[0089] An activation time or isochronal map comprises a contour plot of GI
slow wave activation. An isochronal map may comprise a spatial
representation of the electrode sites, and the isochrones (contour
lines), which represent the spatial distribution of ATs lying within the
same specified time window, i.e. sites with similar activation times. In
a preferred form the temporal resolution (i.e. isochrone interval) may be
about 0.5 seconds when the activity is fast (>10 mm/s), about 2
seconds when the activity is slow (<4 mm/s), and about 1 second when
the activity is from 4-10 mm/s, for example. Information such as speed
and direction of propagation may be inferred from an isochronal map.

[0090] The spatial interval of two neighboring isochrones can be used to
calculate the velocity of slow wave propagation.

[0091] An activation time or isochronal map may be produced by: [0092]
Plotting the identified ATs in the same spatial arrangement as the
electrodes. [0093] Mapping the ATs to the electrodes to which they
pertain, in the same configuration as the electrode matrix. The value of
each AT may be represented by a colour or colour tone in a colour or
colour tone spectrum that represents the appropriate range for the
activation values. A look up `configuration file` may contain information
on electrode distribution and inter-electrode distance; the electrode
numbers may be stored in a matrix, with the corresponding electrode
number reference by the indices.

[0094] A pixelated isochronal map may be converted into a smooth, filled
contour map with isochronal lines spaced at a specified time interval.

[0095] Poor electrode contact to the mucosal surface may result in areas
with imperfect electrical recordings. To represent the entire activation
field, areas with bad contact may be interpolated based on the
surrounding ATs. Inactive electrode sites surrounded by several active
sites are preferably interpolated into the AT map. In a preferred form a
2-stage spatial interpolation and visualization scheme may conservatively
interpolate inactive electrodes using information from neighboring active
electrodes on the basis that if an inactive electrode site is bordered by
three directly adjacent (including diagonal) active electrodes, the AT is
linearly interpolated from adjacent active sites' ATs, and
correspondingly pseudo-colored (an "interpolated site"). If the total
number of active plus interpolated sites bordering a still-blank site is
four, then the still-blank site in interpolated. Such a 2-stage scheme,
as opposed to a recursive one, prevents a run-away interpolation process
from inappropriately filling in blank sites across the entire array.

[0096] FIG. 15a shows a pixelated isochronal map or a part thereof and
FIG. 15b shows such a smooth filled contour map with isochronal lines. In
FIG. 15a black dots indicate electrode sites at which an AT was marked,
and white dots indicate electrode sites for which no AT was marked, but
in some cases was interpolated. The ATs are color coded to propagate from
for example red to blue, representing the earliest and latest ATs
respectively over a 20 second interval from second 217 to second 237. In
FIG. 15b the isochronal lines are spaced at 2 second intervals.

[0097] An isochronal map may also be applied over an anatomical geometry
model in 2D or 3D to aid visualization and accurate diagnosis for the
clinician.

[0098] A velocity field may be mapped in 2D or displayed over anatomical
organ geometry in 3D in a similar way to as described for activation time
mapping. FIG. 16a is an isochronal activation time map, and FIG. 16d is a
calculated velocity field map . . .

[0099] Wavefront Propagation Animation

[0100] The wavefront propagation may be directly animated from the ATs, or
clustered ATs to provide animations of an improved accuracy or clearer
visualization to convey information of a propagation wave behaviour,
including complex behaviors such as occur in slow wave dysrhythmias.
Separate colors may be assigned to the discrete wavefronts in the
animations (or map(s)). In one embodiment, animation may be performed by:
[0101] Configuring a computational array in the same configuration as
the recording electrodes array. [0102] Checking each location on the
recording electrode array at each specified time frame (for example at 1
second intervals), and if an AT occurred at that electrode within that
time frame, then representing the pointer pixel in the computational
array corresponding to the location of the electrode highlighted or in a
different colour than those electrodes at rest. [0103] Causing the thus
`activated` electrode(s) to stay highlighted or coloured for a fixed
duration before turning off again (i.e. going back to `rest`). The
highlighted or coloured point may fade as it disappears. [0104] Different
colours may be assigned to distinct clusters each relating to a discrete
GI electrical wave, for example based on a repeating pattern of a few
colours.

[0105] Animation(s) may also be on an anatomical geometry model to aid
visualization and accurate diagnosis for the clinician as will be further
described. Preferably the animation(s) may be zoomed and rotated.

[0106] Velocity Calculations and Mapping

[0107] GI slow wave propagation velocity in the stomach varies.
Differences may be greater during dysrhythmia. Velocity calculations may
assist in diagnosing at least some dysrhythmias.

[0108] A preferred velocity calculation method comprises a fitting and
calculation process. To calculate a uniform spatially-distributed
velocity field, the ATs from each GI slow wave are first interpolated,
for example using the following second-order polynomial:

T(x,y)={p(1), p(2), p(3), p(4), p(5), p(6)}{x 2, y 2, xy, x, y}

[0109] where T(x,y) is the interpolated activation times at location x and
y in the electrode array. The array of p contains six coefficients for
the second-order polynomial. The AT events in an isochrone map is fitted
in a least-square sense using the following formula:

[0110] where t is the automatically identified activation times of slow
wave events. Matrix $A$ contains evaluated terms using the x and y
coordinates of the corresponding activation time. For solution for p is
solved by using the singular value decomposition of A into V, S, and U
such that,

A=VSU T.

[0111] The search parameters for the number of events included in one wave
are applied over the entire set of electrodes within the isochrone map.
For the description of normal events, the number of active electrodes
within for example a 16×16 array may be adequately fitted by a
second-order polynomial due to the slow moving wave front of the gastric
slow waves.

[0112] Velocity is calculated using the following equation:

V(x,y)={dx/dt; dy/dt}={Tx 2/(Tx 2+Ty 2); Ty 2/(Tx 2+Ty 2)}, where

Tx=dT(x,y)/dx and Ty=dT(x,y)/dy.

[0113] This velocity calculation procedure ensures that the velocity
vector is calculated orthogonal to the wavefront, i.e. representing the
true direction of propagation.

[0114] Less preferably velocity may be calculated via a finite-difference
based derivative estimation from neighbouring electrodes.

[0115] Amplitude Calculation and Mapping

[0116] Extracellularly-recorded slow wave amplitudes may be indicative of
pathology and/or dysrhythmia because amplitudes may be low in some
diseases, where interstitial cell of Cajal networks are degraded and/or
dysrhythmia may be associated with regional high or low slow wave
amplitudes.

[0117] A slow wave amplitude may be calculated based on the identified AT
of an event.

[0119] where S(i) denotes the processed a slow wave signal in a channel at
AT of i. The amplitude is the absolute difference between the maximum and
the minimum in the signal 1.5 seconds, for example, before to 6 seconds,
for example, after the identified TA. This interval captures the entire
duration of the depolarization (down-stroke) the repolarization (return
to baseline) of a gastric slow wave event, while still within the time
interval of a single slow wave event, i.e. unlikely to run into the
signal of the next slow wave event due to the refractory period being
longer than 6 seconds.

[0120] Registration of Device Position and Expansion

[0121] The electrode array position may be anatomically registered in the
GI tract by for example: [0122] The system maybe arranged to display
the position of the mapping catheter in a model stomach geometry which in
conjunction with a displayed an endoscopic view assists the clinician to
position the catheter where desired. [0123] By a second roving anatomical
catheter arranged to a low-current locator signal to a reference
electrode, measuring and transmitting samples, against a 3D referencing
system, for the construction of a geometric matrix or `virtual lumen`.
The position of the mapping catheter and electrode array is also
registered within this matrix by the 2nd catheter. [0124] By imaging
e.g., plain film radiography in 2 axes, and then forming a mesh based on
the identified electrode positions.

[0125] In one embodiment a measuring system is arranged to measure the
volume of air or other fluid installed into an inflatable mapping
catheter via a syringe or pump. The user instills a sufficient volume
until the electrodes press against the gastrointestinal tract mucosa. Air
may also be removed from the tract, via endoscopic suction, such that the
tract walls collapse down around the device. The degree of inflation
determines the final spacing of the electrode array because the
electrodes move further apart during inflation. In a preferred embodiment
the electrode spacing at the time of mapping is determined by: [0126]
The value of air of liquid instilled is measured, for example visually
identified by a volume scale on the syringe or other device used to
effect the inflation. [0127] This volume is input by the user into the
system. [0128] The post-inflation surface area of the device is
calculated by the system. [0129] The spacing of the electrodes at the
time of mapping is calculated by geometric calculations that define the
distance between points on a 3-dimensional surface, with these distances
being proportional to the degree of inflation.

[0130] The calculated `inter-electrode distance` on the expanded device,
at the time of mapping, is subsequently used by the system in calculating
the activation times, clustering, isochrone, velocity, and amplitude
mapping and animations.

[0131] Model Selection from Generic Database, or Subject-Specific Model
Development

[0132] A subject-specific anatomical model of the mapped part of the GI
tract may be produced by for example: [0133] A medical image or image
set providing a 2D or 3D description of an organ position is obtained,
for example via ultrasound, MRI, CT, or plain abdominal x-ray of the
patient. [0134] The GI tract section of interest is extracted via manual
(tracing the organ outline) or automated (determined by imaging density
transition zones) segmentation methods to create a 3D data cloud
representing the surface of the GI tract section. [0135] A finite element
mesh is created to match these data points using a non-linear iterative
fitting method.

[0136] The system may comprise a database of multiple models along with
corresponding data on how each was acquired e.g. sex, age, imaging
methodology, medical history, pathological conditions, and an appropriate
model may be recalled from the database by the system based on data such
as demographic data relating to the patient entered by the clinician, for
example the patients' sex and age data. For example, if a 5 year old
female child is being examined, a mean stomach geometry for five-year old
female children can be automatically presented to the clinician.
Alternatively, a library of models may be stored for review by the
clinician, to manually select one that best matching the stomach geometry
of the patient under examination. This library is arranged in size order
for intuitive browsing.

[0137] Model Construction and Mapping to Model

[0138] Construction of a specific anatomical model brings together:
[0139] registration of the mapping catheter position and degree of
expansion, and [0140] the anatomical stomach geometry model chosen by the
clinician

[0141] to create a model specific for the GI tract section and patient
under evaluation. The chosen anatomical geometry model is reconfigured to
match the calculated geometry resulting from the mapping catheter
expansion, for example by: [0142] The calculated geometry of the
expanded electrode array geometry is used as the `true` reference
geometry, being empirically determined at the time of the procedure.
[0143] The reference model geometry is resized by geometrically expanding
or reducing the model proportions until they match the `true` reference
geometry proportions at the position of the mapping catheter within the
GI tract.

[0144] With a specific model that best represents the anatomy under
evaluation, and the position and degree of expansion of the mapping
catheter, and electrode array, 2D or 3D activation time, velocity, and
amplitude maps and animations may be applied to the model and displayed
as referred to previously. For example this may be achieved by: [0145]
Common landmark points on the model and the locations of the recordings
relative to these landmark points are identified in the model. [0146] The
root mean squared distances between these common points are minimized.
[0147] Activation time, velocity and amplitude maps are "texture mapped"
or orthogonally projected onto the surface of the model. [0148] Results
from multiple recording sites can be combined to enable results from
different regions to be compared in the relative locations at which they
were recorded.

[0149] Analysis Comparison to Database

[0150] The system and method of the invention may facilitate an accurate
diagnosis by allowing the clinician to compare the mapped GI slow wave
data to standard reference (normal population) data. The system may be
arranged to alert the clinician that the mapped characteristics deviate
from the normal range in one or more ways. A specific diagnosis may be
automatically suggested by the system, based on characteristic
differences from the normal population.

[0151] For example to detect low amplitude slow wave activity (low slow
wave amplitudes may theoretically occur in gastroparesis due to
degradation of the interstitial cell of Cajal networks), activation times
in individual slow wave cycles may be identified and amplitudes
calculated. In a user menu in the system interface, the clinician may
select to review slow wave amplitudes for a specific time period of the
recording. As well as spatially mapping the amplitudes for the selected
time period, the system is arranged to perform the following steps to
present a comparison to the standard reference range: [0152] Average
the amplitudes across every slow wave i.e., calculation of a mean and
standard deviation for each cycle. [0153] Average amplitudes across all
waves to generate a mean and standard error of the mean. [0154]
Statistically compare the resultant values to a standard reference
database of normal data obtained from a control population without
gastric pathology (see FIG. 18a below). [0155] Display the result. For
example, if the slow wave amplitudes of the patient with gastroparesis
are statistically found to be lower than that of the standard reference
range, a display item will state this fact. The clinician may note the
finding, and conclude that reduced slow wave amplitudes are a marker of
poor stomach contractility, contributing to a diagnosis.

[0156] FIGS. 17a and 17b show standard reference ranges (normal human
population) of slow wave amplitudes and velocities respectively in
different gastric regions. Note these are serosal reference data, mucosal
data will has lower amplitudes due to signal attenuation by a mucosa, and
a calibration factor must be applied.

[0157] As a further example, to detect dysrhythmic slow wave propagation
(anisotropic slow wave propagation and re-entrant circuits may occur
during dysrhythmia), activation times of individual slow wave cycles are
identified and isochronal activation maps and velocity maps are
calculated for every wave cycle. In a user menu in the software
interface, the clinician may select to review slow wave propagation and
velocity for a specific time period of the recording i.e. specific slow
wave cycles occurring during that period. As well as spatially, mapping
the isochronal activation patterns and velocities for the selected time
period, the system is arranged to perform the following steps to present
a comparison to the standard reference range: [0158] Average the
velocities of each cycle to calculate a statistical mean velocity and
standard deviation for each cycle, and preferably separate the
longitudinal and circumferential velocity components. [0159] Average
velocities across all cycles are calculated to generate a mean and
standard error of the mean for the total velocity, and the total
longitudinal and circumferential velocities. [0160] The resultant values
are statistically compared to a standard reference database of normal
data obtained from a control population without gastric pathology (see
FIG. 18b). [0161] The result is displayed in the software interface. For
example, if the circumferential components of the slow wave velocities of
a patient with functional dyspepsia are statistically found to be higher
than that of the standard reference range (i.e. ˜zero mm/s
circumferential propagation in the normal human antrum, then a display
item indicates this. The clinician may note the finding, and conclude
that an antral dysrhythmia is occurring, contributing to a diagnosis.

[0162] The clinician may then institute a targeted therapy into the
location where the dysrhythmia is occurring, such as pharmaceutical
agent, or pacing or ablation therapy, to interrupt the dysrhythmic
mechanism. The targeting of this therapy can be specifically guided by
the anatomically visualized spatially represented isochronal slow wave
maps, or animations, to ensure it is accurately delivered.

[0163] Gastric Stimulation or Pacing and Entrainment Mapping

[0164] The GI mapping catheter and system may also be used to deliver
targeted stimulation therapy through at least some electrodes for
diagnostic or therapeutic purposes. The stimulation dose and its effects
on GI electrical activity may be measured via the rest of the electrode
array. It may be used in this way to guide stimulation lead implantation,
or for other treatments such as targeted electrical pathway ablation or
drug delivery, for example. The GI electrical activity mapping system and
method of the invention may be used for mapping GI electrical activity
changes resulting from gastric pacing (referred to herein as entrainment
mapping). Gastric stimulation involves delivery of electrical current
into the myenteric layers of the stomach to induce beneficial effects on
nerve function, electrical activity or symptoms. Gastric pacing involves
electrically stimulating the stomach specifically in order to mediate
(entrain) the propagation of GI slow waves for therapeutic purposes.
Gastric stimulation and pacing have primarily been researched for the
treatment of gastroparesis and obesity. In gastroparesis, gastric pacing
may revert gastric dysrhythmias, normalise motility and emptying, and
thereby control symptoms. In obesity, gastric pacing may controllably
disrupt or reverse normal GI slow wave activity, with the aim of
restricting eating and inducing satiety.

[0165] Entrainment mapping allows an accurate spatiotemporal evaluation of
pacing outcomes. The interaction between the native and entrained
activities can be defined by entrainment mapping, dysrhythmias can be
accurately observed, and the area of tissue affected by a pacing protocol
can be quantified across the mapped area. The velocity of slow wave
propagation in all directions can be determined by entrainment mapping.
The changes in amplitude can also be determined by entrainment mapping.

[0166] Entrainment mapping may be employed when applying gastric pacing
via multiple coordinated electrode sites (`multi-channel stimulation`) to
improve the efficacy and energy-efficiency of gastric pacing. Entrainment
mapping may be used to study slow wave behaviours because it enables an
accurate and detailed analysis of multiple local slow wave events
surrounding each stimulus point, and their subsequent interactions.

EXAMPLES

[0167] The invention is further illustrated, by way of example and without
intending to be limiting, by the following description of trials work.

[0171] The SCSI cable connector pins were connected to port A of the
ActiveTwo System (BioSemi, Netherlands). A flexible printed circuit board
mounting a number of electrodes was connected to port B, to allow
validation against a serosal reference electrode.

[0172] A female weaner cross-breed pig of 39 kg was fasted overnight and
anaesthetised. A small midline laparotomy incision was performed and the
prototype device was placed on the serosal surface, for a recording
duration of 5 minutes. The distal stomach was then brought into the wound
and a mini gastric stoma was fashioned. A gastric stoma was used for
insertion of an array of electrodes to contact the mucosa on the interior
of the gastric wall instead of endoscopic access because endoscopic
access is very difficult in the pig due to its restrictive anatomical
configuration in the posterior oropharynx, and a mini-laparotomy was
necessary in any case to perform simultaneous reference electrode
mapping. The PCB carrying reference electrodes was placed over one row of
the mucosal electrodes (palpable through the gastric wall) and a 10
minute recording was taken.

[0173] Unipolar recordings were acquired from the devices at a recording
frequency of 512 Hz. Each device was connected to the ActiveTwo via a 1.5
m 68-way ribbon cable, which was in turn fibre-optically connected to a
notebook computer. Signals from all electrode channels were filtered
using a second-order Bessel low-pass filter of 10 Hz.

[0174] The activation times of the slow wave events were marked at the
point of maximum negative slope. The normalized activation times were
plotted in the same spatial arrangement as the endoscopic prototype and
PCB electrodes. Interpolation of electrodes that had not adequately
recorded the slow wave activation was performed using the linear
interpolation scheme that is programmed in the `linear` method in the
grid data function in Matlab. Three further iterations of uniform linear
interpolations were performed on the activation times to smooth the
isochrones of activation times.

[0175] Isochrones were then calculated from the activation times at 1 or 2
second intervals, showing the timing and direction of slow wave
propagation. In order to calculate a uniform spatially-distributed
velocity field, the activation times from each wave were first
interpolated using the following second-order polynomial:

T(x,y)=p(1)x2+p(2)y2+p(3)xy+p(4)x+p(5)y+p(6)

[0176] where T(x,y) is the interpolated activation times at location x and
y in the electrode array. The array of p contains six coefficients for
the second-order polynomial. A least-square-fitting algorithm was used to
calculate the polynomial coefficients:

[0178] where t is the automatically identified activation times of slow
wave events. The above matrix contains evaluated terms using the x and y
coordinates of the corresponding activation time. The solution for p was
solved by using the singular value decomposition of A into V, S, and U
(A=V SUT). The search parameters for the number of events included in one
wave were over the entire set of electrodes (Δx=99 mm; Δy=27
mm) within a 10 s interval (Δt=10 s). For the description of normal
events, the number of active electrodes within the array was adequately
fitted by a second-order polynomial due to the slow moving wavefront of
the gastric slow waves. Velocity was calculated using the following
equation:

[0179] where V(x;y) is the velocity vector evaluated at coordinates x and
y on the electrode array.

[0180] Slow wave amplitudes were calculated. Where appropriate, slow wave
parameters were averaged over multiple successive waves and expressed as
means±s.d., and Students' t-test was used to evaluate for statistical
significance.

[0181] Subsequently, recording channels 1 and 2 of the catheter were
disconnected from the BioSemi, and reconnected to a stimulator (World
Precision Instruments, Saresota, Fla.), and a continuous bipolar
stimulation protocol of amplitude 3 mA, pulse width period 300 ms and
period 17 s was delivered.

[0182] Results

[0183] FIG. 18 shows a slow wave data recorded from the serosal surface of
the GI tract. The mean serosal slow wave amplitude recorded by the
prototype was 0.20+/-0.06 mV.

[0184] Slow waves were recorded in a number of channels from the catheter
electrodes. FIG. 19 shows slow wave activity and stimulation artifact
recordings taken from the mucosal gastric surface (window=100 s). The top
channel is from an electrode of the mapping catheter and the bottom
channel is from the adjacent PCB reference. The regular sharp peaks
indicated by the upwardly pointing arrows show stimulation artifacts. The
downwardly pointing arrows indicate the slow waves. Evaluation of the
slow wave data confirmed that there was a precise 1:1 coupling of the
interval period between the mapping catheter electrodes and the reference
electrodes. Similarly, the frequency of slow wave events at the mapping
electrodes was the same as the frequency of events in the reference
electrodes. FIG. 20 shows recordings from two adjacent catheter electrode
channels, showing certain slow wave events.

[0185] FIGS. 21a and b show spatial activation maps from two consecutive
waves, demonstrating normal aboral slow wave propagation and computed
velocities of 0.34 cm s-1--FIG. 21a, and 0.31 cm s-1--FIG. 21b,
being consistent with the velocity field measurements calculated from the
serosal refence electrodes (0.39+/-0.06 cm s-1). These were
generated by linear interpolation over the represented electrodes
indicated at 1, according to the array dimensions measured from the
inflated balloon. The dark transverse lines indicate slow wave
propagation and the top-to-bottom arrows the direction of propagation.

[0186] In summary the system was successfully able to register slow wave
activity from the mucosal surface, verified as true slow wave activity
against the reference electrodes, recording simultaneously on the serosal
surface. Spatial activation maps were generated from the
mucosally-recorded data demonstrating the local propagation frequency,
direction, activation pattern and velocity.

Example 2

Trial

[0187] Method

[0188] Flexible PCB multi-electrode recording arrays consisting of copper
wires and gold contacts on a polyimide ribbon base were employed. The
recording head of each array had 32 electrodes in a 4×8 array, at
an interelectrode distance of 7.6 mm.

[0189] Mapping was undertaken in human subjects undergoing upper abdominal
surgery, immediately after laparotomy and prior to additional surgical
dissection. Up to 6 PCBs (192 electrodes; ˜93 cm2) were used
in each experiment, and were held together in ideal parallel alignment.
The recording surface of the PCBs were positioned flush with the anterior
serosal surface of the stomach. The posterior gastric surface was not
mapped. The recording period was 10-15 minutes, usually allowing two
adjacent areas of gastric tissue to be mapped.

[0190] Unipolar recordings of 10-15 min duration were acquired using the
ActiveTwo System (Biosemi, Amsterdam), at a recording frequency of 512
Hz. The common sense (CMS) and right leg drive (DRL) electrodes were
placed on the right upper torso of each patient. Each PCB was connected
to the ActiveTwo in turn connected to a notebook computer. Signals from
all channels were filtered using a second-order Bessel low-pass filter of
10 Hz. Following each experiment, the activation times of the slow wave
events were marked at the point of maximum negative slope. Activation
maps depicting propagation sequences were computed by interpolating the
activation times over the recorded area and using triangulation
techniques to compute isochronal bands. Slow wave velocities were
computed by taking the gradient of the isochronal fields as described in
Example 1 above and slow wave amplitudes were calculated as described in
Example 1 above. Where appropriate, slow wave parameters were averaged
over multiple successive waves and expressed as means and SEM, and an
ANOVA, Students' T-test, or a linear mixed model with a random term for
intercept and site was used to test for statistical significance
depending on the variables that were being compared. The pacemaker region
was defined as the area covered during the first two seconds of slow wave
propagation for the purposes of these statistical correlations.

[0193] The geometry of the stomach of patients was used to create a
subject-specific anatomical mesh, upon which the relevant physiological
data was registered. To develop each patient's mesh, a pre-operative
computed tomography (CT) scan was retrieved and the stomach outline was
digitised on each two-dimensional axial image to form a subject specific
stomach model. The digitised points from each image were then registered
in 3D space to create a cloud of points representing the outline of the
stomach surface. A bicubic Hermite finite element mesh was then used to
represent these digitised points by minimising the orthogonal projections
between each data point and the surface of the mesh.

[0194] The stomach is distensible and its surface dimensions and volume
are dependent on the quantity of contained solids, liquids and gases.
Mapping was performed in the intra-operative state, when the stomach was
empty of solids and liquids and was relatively collapsed. Therefore, in
order to achieve accurate anatomical registration, multiple
intra-operative measurements of the stomach surface were obtained between
fixed anatomical points at the time of mapping, along both the greater
and lesser curvatures and across the transverse organ axis. The specific
anatomical points used were: the apex of the fundus, the boundaries of
the gastroesophageal junction and the pylorus, and the point of the
angularis incisura and its opposite point on the greater curvature
located at approximately 45° from the angularis. Each stomach was
measured during surgery, between points i-vii, and across lines 1 and 2,
as indicated in FIG. 22. These measurements were used to reconfigure the
subject-specific stomach models so that the recorded physiological data
could be accurately registered. The size of each subject-specific mesh
generated from the pre-operative CT scan was then adjusted to match these
intra-operative measurements for each patient.

[0195] For each patient, the PCB placements and physiological data (time
activation maps and slow wave velocity field maps) were registered on the
3D subject-specific model. This was achieved by using a non-linear search
to minimise the distances between at least three common key landmark
points determined during the study (e.g., distances between an electrode
and specified locations on the stomach). The physiological data was then
orthogonally projected onto the surface of the stomach model.

[0196] Results

[0197] The regional velocities of slow wave propagation were averaged for
all patients, and the result was mapped onto a 3D stomach model to
demonstrate a generic visualization. Four activation time and velocity
field maps of pacemaker activity, together with the representative
gastric electrogram recordings used to create these spatial
representations, are shown in FIGS. 23 to 26.

[0198] FIGS. 23a to 26a show stomach models showing the PCB placement.
FIGS. 23b to 26c show individual electrode positions. FIGS. 23c to 26c
are isochronal maps. FIGS. 23d to 26d are velocity maps. FIGS. 23e to 26e
show representative gastric electrogram recordings from the electrodes
used to create the spatial representations.

[0199] Greater than two simultaneous propagating wavefronts were observed
in all patients, and between three and four simultaneous waves were
observed in several cases.

Example 3

FEVT Activation Time Marking

[0200] Slow wave recordings of GI electrical activity were undertaken
during surgery in pigs. Recordings were taken with both a high SNR 48
electrode array (resin-embedded, shielded, silver electrodes) and from a
lower SNR electrode array (flexible PCBs; unshielded), from the anterior
porcine gastric corpus. One 180 second representative data segment was
selected from each of five animals: two segments from the high SNR array
and three from the low SNR array. Unipolar recordings were acquired from
the electrodes via the ActiveTwo System, at a recording frequency of 512
Hz. The common mode sense electrode was placed on the lower abdomen, and
the right leg drive electrode on the hind leg. The electrodes array were
connected to the ActiveTwo which was in turn connected to a notebook
computer. The acquired signals were pre-processed by applying a
second-order Butterworth digital band pass filter. The low frequency
cutoff was set for 1 cpm ( 1/60 Hz); the high frequency cutoff was set to
60 cpm (1 Hz).

[0201] The slow wave ATs in each selected data segment were manually
marked to provide a baseline for comparison. Within the electrode signal
V(t), there are three dominant features of a slow wave event: (1) a small
magnitude upstroke, immediately preceding (2) a fast, large magnitude,
negative deflection (dV/dt˜=1 mV/s), followed by (3) a relatively
long (5 s) plateau phase that decays slowly back to baseline. The fast
negative-going transient corresponds with the depolarization wave front
of the propagating slow wave, signaling the arrival of the slow wave at
the recording electrode site. The point of most negative gradient during
a slow wave was determined to be the AT.

[0202] Automated marking of the low SNR signals was carried out by the
falling edge variable detection method. Some slow wave events exhibit a
relatively fast recovery to baseline. This produces two large pulses in
the transform detection signals, which can lead to erroneous double
counting--the second mark in a set of two should not be marked. Such
double-marking is precluded by imposing a criterion that distinct
activation time events must be separated in time by a minimum value,
termed the refractory period. Also, multiple slow wave events recorded by
an electrode are not identical over time. For example, some pulses in a
particular signal transform detection signals have larger amplitudes than
the others. This amplitude difference can lead to missed detection of the
smaller amplitude events. The FEVT algorithm implements a time-varying
threshold (VT) to aid in the detection of ATs when recorded serosal
waveforms may change over time.

[0203] Use was made of a falling-edge detector signal, E(t), to amplify
the large-amplitude, high-frequency content associated only with negative
deflections, suppressing positive-going transients in the process. It is
formed by convolving the serosal electrical potential signal with an
"edge-detector kernel" dNedge: E(t)=V(t)*dNedge where *
denotes the convolution operator. An edge-detector kernel (Sezan, Comput.
Vis. Graph. Image Process. 49:36-51, 1990), was employed, which is formed
from the convolution of a "smoother" with a "differencer". Nedge
defines the width of the kernel. A fixed value of Nedge=30, a 1-s
wide kernel at fs=30 Hz, were chosen to correspond to the timescale of a
typical large, negative transient. A falling edge (negative transient) in
V(t) produces a positive deflection in E(t) (and vice-versa). When V(t)
remains relatively constant, E(n) is approximately 0. Thus, E(t) is large
and positive when V(t) contains a falling edge, and is negative for a
rising edge. To help focus the slow wave detection algorithm on only the
falling edges in V(t), the (element-wise) product of the smoothed
detection signal S(t) was computed with the falling edge detection signal
E(t), setting all negative values to zero. The resulting signal is termed
the FEVT signal, F(t), which is thus summarized:

[0204] To avoid slight variations in the waveforms leading to some events
escaping detection, the FEVT method incorporated a time-varying detection
threshold. Specifically, the time-varying threshold is based on the
running median of the absolute deviation for time t using a window of
half-width τHW centered at t for the FEVT signal, F(t):

where is the sample mean of F(t) in the time range [t-τHW,
t+τHW] and M{} denotes the sample median, as before. The
variable threshold was then defined as:
Fthresh=η×{circumflex over (τ)}(t), where η is a
tunable parameter, as before. The moving median window was long enough to
include the quiescent period in F(t) between the pulses of energy
associated with the AT, but not so long that one slow wave can unduly
influence the threshold defined for an event occurring much earlier or
later. Values of 15, 30, and 45 s were used, which corresponds to about
1-2 full cycles 3 cpm gastric slow-wave waveform.

[0205] The FEVT method properly handled most problematic signals. For most
electrodes, the FEVT detection algorithm succeeding in finding all ATs,
without finding false positives. The overall performance of the FEVT
algorithm was essentially invariant to the type of signal transform used
when computing the FEVT signal. The FEVT detection signals contained
large positive pulses corresponding to the negative-flanks of the
corresponding electrode signal, while no such pulse was observed for
positive-flank. The FEVT signals had a relatively high SNR. The
time-varying threshold accommodates detection of ATs in an FEVT detection
signal with a variable SNR. The FEVT algorithm was found suited to
properly detect ATs in low SNR mucosally recorded signals.

Example 4

REGROUPS Cycle Clustering Method

[0206] Slow wave recordings were undertaken during surgery in pigs, and
the recordings processed by the FEVT activation time marking method as
described in Example 3. Recordings were taken with a low SNR array
(flexible PCBs; unshielded), from the anterior porcine gastric corpus.
Low SNR platforms were used because mucosal signals are typically of low
SNR.

[0207] Four data sets (120 seconds duration) from four porcine subjects
were selected because these segments represented a range of typical
scenarios as follows: [0208] Normal corpus propagation: Normally,
gastric SWs propagate aborally as a transverse band (or ring) of
activation, and consecutive wavefronts will be simultaneously detected by
a large mapping array. A robust cycle partitioning algorithm must
correctly determine which ATs belong to the distinct cycles, otherwise AT
maps will be highly distorted and misleading. The first test case was
from a corpus recordings on the greater curvature, featuring
simultaneous, consecutive propagating wavefronts. [0209] Normal pacemaker
activity with peripheral region of quiescent tissue: Porcine SWs arise
from a pacemaker area near the greater curvature of the mid-fundus; the
upper and medial fundus are not activated. Robust analysis algorithms
must correctly identify, the concentric propagation, while demarcating
the inactive regions. The second test case was recorded from the porcine
gastric pacemaker site. [0210] Abnormal propagation: Periodic abnormal SW
behaviors are observed during porcine HR gastric mapping often
characterized by retrograde propagation and/or ectopic pacemaking. Robust
analysis methods must correctly identify abnormal propagation patterns.
The third and fourth test cases were selected from data sets exhibiting
retrograde propagation and ectopic pacemaking, recorded from the upper
corpus/distal fundus. Importantly, the latter three of these test cases
also had patchy data quality, which results from suboptimal or obstructed
electrode contact, or due to interfering signals (e.g., respiration
artifacts). [0211] Competing pacemakers/clashing wavefronts: When more
than one region acts as a pacemaker, the multiple corresponding
wavefronts generated by them will collide. Such dysrhythmic activity may
correspond to clinically diagnosable conditions. Robust analysis methods
must correctly identify that a single cycle contains multiple clashing
wavefronts.

[0212] The REGROUPS algorithm works by clustering (x, y, t) points
representing ATs into groups that represent independent cycles ((x, y)
denotes the position of an electrode site (relative to an arbitrary
reference), and t denotes an AT marked at that site). The algorithm is
initialized by creating a master list of all marked ATs, and selecting
the master seed electrode site in automated fashion (see below). A queue
containing the (x; y) positions of nearby sites is established. A
"nearby" site was defined as falling within a distance {square root over
(2)}dmin of the seed electrode, where dmin denotes the minimum
distance between the seed site and the closest site containing (at least)
one AT. The factor of {square root over (2)} essentially defines a
circular search radius (for a square lattice array) to include sites
located diagonal to the seed. dmin is not necessarily equal to the
inter-electrode spacing (although it often will be), enabling the
algorithm to successfully "jump" across local patches of missing data.

[0213] REGROUPS also employs an iterative "flood fill" or "region growing"
procedure. The first queue entry (electrode site) becomes the current
seed, and all ATs at that site, AT(x; y; j) (where j=1, . . . , J indexes
the marked ATs), are tested for membership. A point (x; y; t) in AT(x; y;
j) is assigned membership to the cluster (or not) based on comparison to
an estimated AT, Test. If the difference is small enough, the AT
which minimizes the estimate error is assigned membership to the cluster:

min j | AT ( x , y , j ) - T est ≦ Δ
t max .. ##EQU00005##

Once assigned, membership is never revoked. A point can be assigned
membership to only one cluster (at most): Upon assignment, that (x; y; t)
point is removed from master list of ATs so that is never tested again
during the remainder of the clustering process. If the tested point is
clustered, all of its nearby neighbors are added to the back of the
queue, if they are not already in it. If the tested point is not
clustered, it may be tested again for membership only after new cluster
has initialized (a new activation time surface is calculated) at the next
iteration. This restriction forces all wavefronts to be independent.
Regardless, of whether any point was added to the cluster, the current
seed is removed from the queue, and the next queue element becomes the
current seed. Thus, the region in (x, y, t) space representing an
independent cycle grows, terminating when the queue of nearby points
becomes empty. At this stage, the cluster contains all ATs from one
cycle. The same process is repeated anew to identify another independent
cycle, starting with the next sequential AT marked at the master seed.
Each iteration produces a cluster of (x, y, t) points, which represent
the dynamics of an independent cycle. Points which are not assigned
membership to any cluster are termed "orphans."

[0214] A step is to implement a 2nd-order polynomial surface, T(x, y), to
act as a continuously updating spatiotemporal filter, where:
T(x,y)=p1x2+p2y2+p3xy+p4x+p.sub.5y+p6.
Using only the (x, y, t) already in cluster, the vector of coefficients
that defines the surface, p=[p1, p2, p3, p4, p5, p6], is computed using a
previously described least-squares-fitting procedure:
p=(ATA)-1At where A is a matrix whose rows are created using
the (x, y) electrode positions of points already in the cluster:
[x2, y2, xy, x, y, 1]; and t is a column vector containing the
corresponding ATs marked at those electrode sites. Having solved for the
vector of coefficients p that defines the polynomial surface, an estimate
of the AT at a nearby site (xn, yn) can be obtained by simply
extending the surface into that region: Test=T(xn, yn).
The coefficients describing the surface, p, are automatically updated
every time another point is added to the cluster. Therefore, the data set
at hand determines the form of the polynomial surface, making it
substantially more robust and more widely-applicable for distinguishing
independent cycles in a variety of SW behaviors. At least 6 points are
required to obtain a fully determined system of equations, so prior to
switching on the polynomial surface estimation, is computed as the mean
of the ATs of the points already assigned membership in the cluster. In
practice, we found the algorithm performs best when the polynomial
surface estimation is switched on when the cluster size reaches a
"critical mass" of at Ncrit≧12 points, which is on the order
of frac110 the total number of electrode sites on the recording platform
(data not shown). If the critical mass is too small, then the surface was
overfit to a small core of points, yielding a poor description of the
propagation pattern across the entire electrode array. On the other hand,
if the critical mass was too large, then the technique fails to utilize
information about the velocity gradient at the wavefront boundary, which
is critical for the success of the algorithm (other spatiotemporal
filters may be introduced into the software to aid detection of different
electrical patterns).

[0215] The outcome of clustering is dependent on the initial seed
selection, particularly when the data quality is patchy (sparse). Seed
selection was automated such that the seed was chosen to be at an
electrode position (x, y)seed which is typically embedded in a
region providing the maximal density of information about the propagating
wavefront: [0216] For each electrode site, tally N(x, y), the total
number of ATs detected at an electrode site location (x, y). [0217]
Compute the center of mass (CM) (xCM, yCM) using the entries of
N(x, y):

[0217] x CM = i N ( x i , y i ) x i
i N ( x i , y i ) ##EQU00006##

where the sum is taken over all electrode sites, indexed by i. The
y-coordinate yCM is similarly computed. [0218] Check if (xCM,
yCM) corresponds to the coordinates of an electrode with marked ATs.
If yes, then the seed is selected to be the CM. If not, move the seed to
the closest electrode site meeting this condition. In practice, the seed
is usually selected to be at the CM.

[0219] Isochronal slow wave activation maps were generated. Control and
experimental arms were developed to compare completely automated versus
completely manual results, starting from raw data and ending with AT
maps. This approach therefore sought to validate the
FEVT-REGROUPS-Automated-Isochronal-Mapping pipeline, to demonstrate real
world practicability of the complete system: [0220] experimental arm:
ATs were identified via the FEVT method. The REGROUPS and automated
isochronal mapping algorithms were applied to each FEVT auto-marked data
set to identify the first 5 consecutive SW cycles. [0221] control arm:
ATs were manually assessed and marked by a fully blinded manual marker.
ATs were manually marked at the apparent point of steepest negative
slope. The resulting ATs were then manually partitioned to identify the
first 5 consecutive SW cycles, and resultant isochronal maps generated.
The manually generated maps were considered to be the standard for
comparison.

[0222] Quantitative comparison: The automated results were quantitatively
compared to the manually-derived results in terms of AT mapping a) area
of coverage, and b) isochronal timing accuracy. The REGROUPS results
showed strong similarity to the manual results with comparable isochronal
intervals and orientations, comparable map coverage, and a high
consistency between cycles. For normal pacemaker activity and peripheral
quiescent region the REGROUPS results proved similar to the manual
marking results with comparable isochronal intervals, orientations, and
consistency between cycles, and similar spatial map coverage. For
abnormal activity the manual maps and REGROUPS maps were highly
comparable in terms of isochronal intervals and orientations. The
REGROUPS consistently demonstrated slightly greater spatial coverage than
the manual maps, extending proximally with a physiologically-consistent
activation pattern.

Example 5

Gastric Pacing

[0223] Weaner pigs of either sex and of mean body weight of 36.1±2.6 kg
were fasted overnight, before anaesthesia. The pigs were placed supine on
a heating pad and laparotomy was performed.

[0224] Pacing was performed using a DS8000 stimulator (World Precision
Instruments, Sarasota, Fla., USA) attached to two stainless-steel 23 g
pacing needles (8 mm separation; 1.6 kΩ tissue resistance). All
pacing protocols employed in this study were bipolar, involving constant
current pulses of period 17 s-19 s, amplitudes of 2 to 4 mA, and a pulse
width of 400 ms. Baseline recordings were taken prior to stimulation, and
each protocol was evaluated for a duration of 5-20 minutes. The pacing
needles were positioned in either the upper greater curvature, the distal
antrum, or in the mid-corpus. The mid-corpus pacing site was employed to
enable the study of entrained slow wave propagation in all directions
from the stimulation site. The specific protocol used in each example
study is described with the associated results.

[0225] HR mapping was performed using flexible printed circuit board PCB
electrode arrays as described in Example 2 above. Signal analysis was as
described in Example 2. Isochronal activation maps of selected
propagation sequences were computed and velocity field maps for selected
sequences were computed. Slow wave amplitudes were calculated. Where
appropriate, slow wave parameters were averaged over multiple successive
waves and expressed as means±s.d. Students' t-test was used to compare
slow wave parameters, with a p-value<0.05 considered to be
significant. An HR analysis allowed pacing outcomes to be evaluated at
any pacing frequency, because the density of electrodes allows the slow
wave propagation sequences to be tracked at superior spatial resolutions,
allowing the spatial origin of pacing onset to be located precisely.

[0227] The foregoing describes the invention including embodiments and
examples thereof, and alterations and modifications are intended to be
incorporated in the scope hereof as defined in the accompanying claims.